Does replacing 3x3 filters with 3x1 and 1x3 filters improve the performance?
If the filter is separable, that is, the NxM kernel can be mathematically equal to the convolution of a Nx1 filter and a 1xM filter, there are a very important increase in performance.
Using separable convolution, the network can made an optimal usage of the shared memory and of the parallelism in memory access. See this excellent article for details. These improvements are bigger for bigger kernels.
Also the training is improved, starting by the simple fact that a NxM filter has a number of parameters proportional to N*M but the related separable one has N+M.